You are here

BigData@CSAIL Lecture Series with Jeremy Freeman

We want to understand how brains work. New technologies let us measure and manipulate neural activity, at the scale of large populations or entire brains, in behaving animals. But this in turns yields a new challenge — how to make sense of our data. In this talk, I highlighted the difficulties posed by these data, especially the need for parallelization over multi-dimensional arrays, and for exploratory visualization. And I described an ecosystem of open source technologies for flexible, scalable, and sharable analysis that let us rapidly analyze results, design new experiments, and collaboratively interpret. This effort stands at the intersection of several exciting disciplines, and promises to begin to reveal the fundamental operating principles of the brain.

Biography:

Jeremy Freeman is a neuroscientist using computation to understand the brain. He obtained his BA from Swarthmore College in math, biology, and psychology. He completed a PhD in neural science at New York University, and is currently a Group Leader at HHMI’s Janelia Farm Research Campus. Freeman develops new approaches for analyzing, visualizing, and understanding large-scale patterns of neural activity. He hopes to reveal the deep principles according to which all brains function, including our own.